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The dimensionality of the 17 items from the motivation scale was analyzed using PCA.
The dimensionality of the 17 items from the motivation scale was analyzed using principle components factor analysis (PCA).
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The connections between depression (as measured by the CIDI-SF) and components of personal stigma (as measured by the "Depression is a matter of will -scale, the "Desire for Social Distance"-scale and the "Antidepressant Attitudes" - scale) will -scaleed using logisthe regressions.
Differences in the reduction in pain (Likert scale) were analyzed using an analysis of covariance with treatment group, baseline Likert scale score, and baseline BMI as covariates, while differences in joint tenderness, swelling and erythema were assessed using proportional odds regression with treatment group, baseline physician assessment, and baseline BMI as covariates.
Internal consistency for the summative scales was analyzed using Cronbach's alpha and values are presented in Table 1.
The scale development process, psychometric properties, feasibility, and implementation of sedation scales were analyzed using a 0-20 systemg system.
The multiscale problem, which involves both macroscopic and microscopic length scales, is analyzed using asymptotic expansion homogenization coupled with the finite element method.
The six scales were analyzed using OLS-regression.
Variables with categorical scales were analyzed using percentages and absolute frequencies.
Quantitative data from categorical variables including Likert scales were analyzed using descriptive and inferential statistics with SPSS version 20.
In accordance with established conventions of assessment tool development, the internal structure and dimensionality of the networking scales were analyzed using a factor analysis approach.
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